| """Pydantic domain types — the shapes business logic reads. |
| |
| ORM rows live in `store/models.py`; this file is the layer the |
| Orchestrator / tools / API touch so we never leak SQLAlchemy types |
| upward. Spec: docs/Specs.md §9. |
| """ |
|
|
| from __future__ import annotations |
|
|
| from datetime import datetime |
| from typing import Literal |
|
|
| from pydantic import BaseModel, ConfigDict, Field |
|
|
| UserRiskTier = Literal["new", "trusted", "neutral", "watched"] |
| Personality = Literal["strict", "balanced", "lenient"] |
| TierOverride = Literal["auto", "fast", "standard", "deep"] |
| StrategyTier = Literal["FAST", "STANDARD", "DEEP"] |
| ToolStatus = Literal["success", "failure", "skipped", "timeout"] |
| InvestigationStatus = Literal["pending", "completed", "failed"] |
| ModAction = Literal["REMOVE", "APPROVE", "ESCALATE", "LOCK"] |
| FeedbackSource = Literal["verdict_card", "reddit_native"] |
|
|
|
|
| class SubredditProfileRow(BaseModel): |
| model_config = ConfigDict(from_attributes=True, extra="ignore") |
| subreddit_id: str |
| name: str |
| personality: Personality = "balanced" |
| rules: str = "" |
| region: str = "Global" |
| cold_start_count: int = 0 |
| show_cost_in_dashboard: bool = False |
| kill_switch: bool = False |
| tier_override: TierOverride = "auto" |
|
|
|
|
| class UserMemoryRow(BaseModel): |
| model_config = ConfigDict(from_attributes=True, extra="ignore") |
| subreddit_id: str |
| user_id: str |
| risk_tier: UserRiskTier = "new" |
| prior_violations: int = 0 |
| prior_approvals: int = 0 |
| last_seen_at: datetime | None = None |
| detail: dict[str, object] = Field(default_factory=dict) |
|
|
|
|
| class ThreadMemoryRow(BaseModel): |
| model_config = ConfigDict(from_attributes=True, extra="ignore") |
| subreddit_id: str |
| post_id: str |
| mod_actions_taken: list[dict[str, object]] = Field(default_factory=list) |
| participants_count: int = 0 |
| last_summary: str = "" |
| last_summary_at: datetime | None = None |
| detail: dict[str, object] = Field(default_factory=dict) |
|
|
|
|
| class StartInvestigationInput(BaseModel): |
| """What `start_investigation` needs to create a pending row.""" |
|
|
| model_config = ConfigDict(extra="forbid") |
| correlation_id: str |
| subreddit_id: str |
| target_kind: Literal["comment", "post"] |
| target_id: str |
| target_body: str = "" |
| target_author_id: str = "" |
| tier: StrategyTier |
|
|
|
|
| class FinalizeInvestigationInput(BaseModel): |
| """Verdict fields written when the pipeline completes.""" |
|
|
| model_config = ConfigDict(extra="forbid") |
| risk_tier: Literal["HIGH", "MEDIUM", "LOW"] |
| recommendation: Literal["REMOVE", "APPROVE", "ESCALATE", "LOCK", "NO_RECOMMENDATION"] |
| calibrated_confidence: float = Field(ge=0.0, le=1.0) |
| rationale: str |
| confidence_breakdown: dict[str, float] |
| model_reasoner: str |
| model_summarizer: str |
| cost_usd: float = Field(ge=0.0) |
| latency_ms: int = Field(ge=0) |
| input_tokens: int = 0 |
| output_tokens: int = 0 |
| validation_flag: bool = False |
| degraded: bool = False |
| cold_start: bool = False |
|
|
|
|
| class EvidenceRowInput(BaseModel): |
| """One Evidence Accumulator entry to persist.""" |
|
|
| model_config = ConfigDict(extra="forbid") |
| evidence_id: str = Field(pattern=r"^ev-\d+$") |
| tool: str |
| summary: str = "" |
| detail: dict[str, object] = Field(default_factory=dict) |
| status: ToolStatus = "success" |
| latency_ms: int = Field(ge=0, default=0) |
|
|
|
|
| class FeedbackInput(BaseModel): |
| """Mod action alignment — recorded by the verdict-card buttons + onModAction.""" |
|
|
| model_config = ConfigDict(extra="forbid") |
| correlation_id: str |
| subreddit_id: str |
| target_id: str |
| mod_action: ModAction |
| raw_action: str = "" |
| moderator_id: str = "" |
| moderator_name: str = "" |
| source: FeedbackSource |
| aligned: bool | None = None |
|
|
